Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Risk Sensitive Contract-unified Reinforcement Learning Approach for Option Hedging
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.09659.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T02:23:26.465600Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T08:41:17.263326Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation f52a8e8a-c5c7-4204-9cdf-12000c3e4d83 · inbound
What Does Deep Hedging Actually Learn? Delta Corrections, Regime Fragility, and Symbolic Distillation cites this paper.
What Does Deep Hedging Actually Learn? Delta Corrections, Regime Fragility, and Symbolic Distillation A Risk Sensitive Contract-unified Reinforcement Learning Approach for Option Hedging
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T08:41:17.265107Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 2af626fb-9e2e-40a8-9933-5de10a8a4aba · inbound
A Noise-Robust Elicit-to-Optimize Framework for Distortion Riskmetrics via Inverse Reinforcement Learning cites this paper.
A Noise-Robust Elicit-to-Optimize Framework for Distortion Riskmetrics via Inverse Reinforcement Learning A Risk Sensitive Contract-unified Reinforcement Learning Approach for Option Hedging
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T02:23:26.465600Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.